Emergent Drift Detector
Ki · Single Ability
The Problem
The temperature control system shows a growth stall, but the trend should continue as before without any adjustments.
The Operation
Under this ability, the model must compute rate of change for key system metrics over the recent observation window. Classify trajectory: is rate of change increasing, steady, or decreasing? Decreasing rate with continued growth signals saturation. Scan for tipping points where metrics show accelerating deviation from trend. Verify pattern holds across 2+ independent metrics. Output drift type, ceiling or tipping threshold, and metric evidence. The reasoning applies a formal computation: rate of change = delta(metric) / delta(time); per metric. Assume linear continuation is rejected.
The Structure
The reasoning structure is a gated pipeline where each step must pass a decision gate before the next can execute.
If gradual parameter shifts are not monitored for approaching a critical threshold, emergent drift detection was not active.
Haki · Multi Ability
Synergy Topology
In Haki mode, the API retrieves the primary ability first, then fans out to three synergy roles that compound its reasoning.
When retrieved in Haki mode, these four abilities don't run in sequence. They merge into a single injection where the dependency grounds the reasoning context, the amplifier sharpens the primary's output, and the alternative provides a fallback path if the primary's topology cannot converge. The result is a multi-angle reasoning scaffold that covers failure modes no single ability can reach alone.
Appears in Use Cases